For the following set of data, 3 5 5 10 10 22 8 17 4 15 7 13 Compute the Pearson correlation. Determine if there is a relationship, what type of relationship it is, and how strong or weak that relationship is, if any relationship exists. Find the linear regression equation for predicting Y from X (use the linear regression equation formula #1 from class handout). Use the regression equation that you derived (part b above) to compute the predicted Y for each actual value of X. Compare the predicted Y scores to the actual Y scores. Why is there a difference between the predicted Y values and the actual Y values? How do you explain this difference? a. b.
Correlation
Correlation defines a relationship between two independent variables. It tells the degree to which variables move in relation to each other. When two sets of data are related to each other, there is a correlation between them.
Linear Correlation
A correlation is used to determine the relationships between numerical and categorical variables. In other words, it is an indicator of how things are connected to one another. The correlation analysis is the study of how variables are related.
Regression Analysis
Regression analysis is a statistical method in which it estimates the relationship between a dependent variable and one or more independent variable. In simple terms dependent variable is called as outcome variable and independent variable is called as predictors. Regression analysis is one of the methods to find the trends in data. The independent variable used in Regression analysis is named Predictor variable. It offers data of an associated dependent variable regarding a particular outcome.
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